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I'm new in fuzzy logic modeling. I'm using the package "sets" in R. Starting form a database of crisps variables of 8 input varialbes and 1 output variable, I performed the fuzzyfication and I assigned a membership function to each variables (inputs and output). I'm now stucking with the definition of the fuzzy rules.

I would like to ask if we have the same consequent from different rules, how are these rules processed? I read that it's possible for this problem to assign a weight to each rule? Is it the correct way to proceed? There's some one how has already experiences with this issue?

Thanks a lot in advance. Michele

Michele MORETTI
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  • As written this isn't a very specific programming question so it's not quite appropriate for this site. Perhaps you could provide a [reproducible example](http://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example) to make the programming question clearer. Or if this is really about statistical modeling, consider asking your question at [stats.se] instead. – MrFlick Apr 27 '16 at 13:47
  • Thanks a lot MrFlick! – Michele MORETTI Apr 28 '16 at 12:12

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it is possible to assign rules with two different antecedents to the same output. I have previous Matlab experience, not R, but it is the same principle everywhere and the system is evaluated like a charm. However, be careful if you want to use neurofuzzy network (ANFIS), because it doesn't allow the particular characteristic.

brbtsl
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